The Influence of Client Risks and Treatment Engagement on Recidivism

Abstract

The current study modeled 12-month postrelease rearrest (recidivism) in terms of pretreatment risk factors (i.e., criminal history, criminal thinking,) and during-treatment engagement in a sample of 653 subjects admitted to four prison-based substance treatment programs. Structural equation modeling was used to test during-treatment engagement as a mediator variable in explaining the relationship between the pretreatment risk factors and recidivism. Results indicated that (a) a long history of criminal conduct correlated with criminal thinking, which in turn had a significant negative relationship with engagement in treatment; (b) the level of criminal involvement had a significant positive relationship with rearrest, whereas the level of criminal thinking did not influence being rearrested directly; (c) the relationship between criminal history and rearrest was partially mediated by criminal thinking and treatment engagement, whereas the relationship between criminal thinking and rearrest was fully mediated by treatment engagement. The findings suggest that it is important to design interventions targeting criminal thinking and monitor treatment engagement as an indicator of treatment performance. Clinical implications also include the importance of facilitating treatment engagement and the utility of conducting prognostic assessment to inform treatment.

KEYWORDS:

• criminal history
• criminal thinking
• risk factor
• treatment engagement
• recidivism

Acknowledgments

This work was funded in part by the National Institute on Drug Abuse (NIDA; Grants R01DA025885, 2U01DA16190, and 5R01DA013093). The interpretations and conclusions, however, do not necessarily represent the position of the NIDA, the National Institutes of Health, or the Department of Health and Human Services. More information (including data collection instruments that can be downloaded without charge) is available online at ww.ibr.tcu.edu, and e-mail can be sent to [email protected].

Notes

^a Results of the Chi-squared test indicated that the distribution of participants in race groups was different between genders, χ²(2) = 58.29, p < .001. Because the number of participants coded as “Other” race was smaller than 5, that race group was excluded in the chi-squared test.

^b The independent t-test indicated that there was no difference in age between males and females, t = 0.88, p = .38.

^a Age and gender are two covariates.

*p ≤ .05. **p < .01. ***p < .001.